System and method for testing software applications in a software defined network

ABSTRACT

A system, method and computer-readable medium for testing a service-based application identifies a set of use cases for the service-based application. Each use case in the set is mapped to a test case to generate a first set of test cases. Each of the test cases is refined to generate an updated set of test cases and the updated set of test cases is executed.

TECHNICAL FIELD

The present disclosure relates generally to software testing and verification. More particularly, the disclosure relates to methods and systems for automatically testing software applications in a software defined network.

BACKGROUND

In Software Defined Network (SDN) development environment, Agile or DevOps methodology and Continuous Integration (CI) are usually required. Agile software development relates to an approach for software development under which requirements and solutions evolve through the collaboration of cross-functional teams. Agile development promotes adaptive planning, evolutionary development, early delivery, and continuous improvement, and facilitates rapid and flexible response to change. Hence, these approaches are becoming more and more popular, and have been adopted by SDN software and network application development companies as a means of improving the quality of software, and reducing the amount of time it takes to deliver the software.

SDN Software-defined networking (SDN) is an umbrella term encompassing several kinds of network technology aimed at making the network as agile and flexible as the virtualized server and storage infrastructure of the modern data center. Due to the programmability of SDN, the risk of bugs and challenges for testing has been increased. As a result, the quality of SDN control software and network services actually determine the reliability of SDN.

Currently, testing is performed using a Model Based Testing approach. Model-based testing is an application of model-based design for designing and executing artifacts to perform software testing or system testing. Models can be used to represent the desired behavior of a system under test, or to represent testing strategies and a test environment. Because test suites are derived from models and not from source code, model-based testing is a form of black-box testing. The current Model-Based Testing based on the system description for application under test as finite state machines to generate test cases depending on the complexity of system under test, the corresponding model still could be very complicated and hard to use in real word.

Software correctness verification is a complicated subject. From a pure correctness verification perspective, people look for program invariants, and use Predicate Abstraction on the state space of program variables, Model Check etc. to verify its correctness. Program invariants are conditions that can be relied upon to be true during execution of a program, or during some portion of it. A program invariant is a logical assertion that is held to always be true during a certain phase of execution. For example, a loop invariant is a condition that is true at the beginning and end of every execution of a loop. The invariants are usually hard to find and for a middle-scale program usually has a large variable/predicate state space. With these difficulties, automated correctness verification is not used outside of a laboratory environment. From black-box testing perspective, methods to automatically verify service correctness for the SDN software are not available.

Currently test cases are usually managed by testers. Each person has his/her own test cases so that later on, the regression tests are sometimes hard to perform because there are no complete test scripts for a given release delivery. Often testers have to rewrite regression scripts to test same things which previously have been tested by others.

Currently tests typically use simulated data to do load/stress tests. This is because of lack of real data for systems. Many real world scenarios may not be tested so that the problems have to be faced after production deployment.

There is a need to provide methods for testing SDN software that avoids the disadvantages inherent in the model-based testing approach. There is a need to provide methods for testing SDN software that do not rely on program invariants to verify the correctness of the SDN software. There is a need to provide methods for testing SDN software that can be made available to a variety of users. There is a need to provide methods for testing SDN software that use real-world data to identify problems that have to be faced after production development.

SUMMARY

To achieve the foregoing, one embodiment provides a method of testing a service-based application including: identifying a set of use cases for the service-based application, mapping each use case in the set of use cases to a test case to generate a first set of test cases, refining each of the test cases in the first set of test cases to generate an updated set of test cases, and executing updated set of test cases. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

Another general aspect includes a system for testing a service based application including: a computer system, a test case generator associated with the computer system for generating executable test cases with propositional statements, a test case interpreter for interpreting the propositional statements generated by the test case generator by checking a state of services under test, a service specification acquisition module for acquiring all service specifications, and a basic functions library associated with the computer system.

One general aspect includes non-transitory computer readable medium including computer executable instructions embodied in a computer readable medium and when executed by a processor of a computer performs steps including: identifying a set of use cases for a service based application, mapping each use case in the set of use cases to a test case to generate a first set of test cases, refining each of the test cases in the first set of test cases to generate an updated set of test cases, and executing the updated set of test cases.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a framework architecture for testing application systems.

FIG. 2 is a block diagram illustrates the relationship between application services and application under test.

FIG. 3 is a flowchart of a method for testing a software application.

FIG. 4 is a flowchart of a method for generating test cases.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

From a black-box testing perspective, the service states determine the state of the application so instead of describing the application under test as a finite state machine, one may identify the service-flow in a Use Case/Use story of requirement and input & output conditions to generate an executable test case with propositional formulas. When a test case runs, these formulas are interpreted based on related service states to verify if those formulas are satisfied. A test case library is provided to help implement test cases universal management. For a given software release, there is a set of executable test cases in a test case library corresponding to use cases of requirements. As such, regression tests are very easy to be carried out. A solution to load/stress tests is to provide testers ability to look at historic data in production databases. Statistic tools could be used to pinpoint the application peak hours and the related data can be extracted from database and schedule to reapply to the application being tested. Since original timing and concurrency are kept, many real world scenarios can be tested in this way before production deployment.

In an embodiment a new black-box testing framework for testing a service-based application systems is provided, where a service type is either representational state transfer (REST) (recommended by OpenFlow for SDN northbound interface) or Simple Object Access Protocol (SOAP) to meet the needs of SDN network applications testing for the northbound interface and traditional web services.

An embodiment of the testing framework provides:

-   -   Conversion of service-flow with input/output constraints in         requirement to executable test cases with a group of         propositional logic formulas;     -   Interpretation of formulas at test case run-time to implement         Verification Automation (VA);     -   Management of generated test cases centrally in test case         library so that regression tests can be performed effectively         and efficiently; and     -   Utilization of historical data in production database for         load/stress tests so that many real world scenarios can be         tested before production deployment

The Framework Supports Functional Tests, Load/Stress Tests and Regression Tests

FIG. 1 illustrates a framework architecture 100 for testing application systems.

The Framework Architecture 100 Includes Framework 101.

The framework 101 includes a test case generator (TC generator 103). TC generator 103 generates executable test cases by mapping a use case to a group of test cases, with propositional statements (p→q logic structure) being abstracted from the corresponding service-flow and service input and output conditions. This can be done either automatically or manually depending upon the needs.

The framework 101 includes a test case interpreter (TC interpreter 105). TC interpreter 105 interprets the propositional statements, when a test case is run, by checking state of services under test to perform verification steps automatically. The final evaluation of the propositional statements determines a success or failure of the test case. When all services in service-flow return a success, the test case is passed. If, on the other hand, there is a failed service, TC interpreter 105 terminates interpretation of the test case and returns with the failed service information. TC interpreter 105 also performs lexical, syntactical and type check on the test case and invokes basic functions from a built-in library (BF library 111).

The framework 101 includes a service specification acquisition module 107 that acquires all service specification from Application Design 121 (where the application architecture and service implementations design are specified) and Application Interface Design 123 (where interface requirements for one application to another are specified), creates corresponding service classes with attributes of the service, attributes of testing such as service type, URL and protocol string format, and method of testing like get, send, etc. A service class consists of attributes including all fields with possible values of service request and response, service types such as SOAP, REST etc., with format of XML, JSON etc., service network address for request to send, and methods to process data of attributes. These generated service classes are saved on service object store 109 and are ready to be accessed by TC_Interpreter 105.

The framework 101 includes BF library 111 that archives a set of basic functions that are developed by testers to support all functionality of the framework 101.

The framework 101 includes a user interface 113 that may be a graphical user interface (GUI), which is used for users to interact with the framework 101. Use cases and use stories can be entered here and then abstracted into service-flow with input and output conditions.

In operation, data from a new release 117 may be used to develop a high level design 119 which in turn may be provided to user interface 113. Information from an advance design 121 or an application interface design 123 may be provided to service specification acquisition module 107 for creating all service specifications. The service specification acquisition module 107 is used to extract service requirement specifications and other service related information from AD and AID documents. For example, all fields and possible values of a service request and response are extracted from AID by this module. Data from the service specification acquisition module 107 may be stored in service object store 109. The TC generator 103 may receive data from service object store 109, user interface 113 or from test cases 125. The output of the TC generator 103 may be stored in the BF library 111. TC interpreter 105 may exchange data with BF library 111, test cases 125 or application under testing module 129 and may receive data directly from test case library 127. The TC interpreter 105 will provide data to simulator module 115 which may also exchange data with the application under testing module 129. The simulator module 115 is used for simulating the required service request or response in testing when a real service is not available. The TC interpreter 105 may also provide data to the test results report module 131.

FIG. 2 illustrates the relationship 200 between service and application under test. The application under test 203 may have a plurality of application processes under test (many to one relationship). The application under test 203 may have a plurality of services associated therewith (one to many relationship). For each service 205 there may be a plurality of service types 207 (many to one relationship) and each service type 207 will have a service request 209 (one-to-one relationship). Each service request 209 will have a service response 211 (one-to-one relationship).

FIG. 3 is a flowchart of an application testing method 300 for testing an application design.

In step 301 the application testing method 300 identifies the service flow and converts the service flow into a use case/user story. From a functional test perspective, a service based application may be taken as a series of services S1, S2, . . . , Sn, where N is the total number of services. Let S be an instance of a service class. From black-box testing perspective, a successful service is equivalent to a condition where both of service request and service response meet service requirements In other words, service S is TRUE if and only if input of service (S.in) adheres to requirements (for both REST and SOAP services), the S.in is applied to the service S, output of service (S.out) is received by requester, and the S.out adheres to requirements.

In step 303 the application testing method 300 maps the use cases/user stories into a first set of executable test cases with propositional formulas. Each of use cases in HLD/user stories in Agile is mapped to test cases.

For each of use cases/user stories the method 300:

-   -   Identifies conditional (IF-THEN-ELSE-like and/or CASE-OF-like)         branches;     -   Identifies service-flow for each of branches;     -   For each of branches, identifies input conditions and output         conditions;     -   Maps each of branches to one test case; and     -   Identifies propositional statements as verification logic for         the test cases based on input and relating services.

The following are some examples of mapping Use Cases to Test Cases

Sample Use Case 1 { IF the “eventDomain” field of triggering alarm is “fault” Query the mob_aots_tickets table where: mob_aots_tickets.AlarmSourceName = @eventSourceName of triggering fault AND mob_aots_tickets.OriginalProblemAbstract = @alarmCondition of triggering fault AND TicketState != “Closed”|”Cancelled” IF the “eventDomain” of triggering alarm is “thresholdCrossingAlert” Query the mob_aots_tickets table where: mob_aots_tickets.AlarmSourceName = @eventSourceName of triggering TCA AND mob_aots_tickets.OriginalProblemAbstract = @alertDescription of triggering TCA AND mob_aots_tickets.TicketState != “Closed”|”Cancelled” IF a record is returned: Get ticket number and ActiveOrg from record Update this AOTS-TM ticket IF a record is not returned Create a ticket into AOTS-TM } Based on conditional branches of the value of eventDomain, the following test case can be generated first.

-   -   Test Case: (Conditional branch for eventDomain of triggering         alarm=fault when Ruby-M receives a UEB DCAE alarm)     -   if eventDomain of triggering alarm=fault     -   Query mob_aots_tickets database table if         mob_aots_tickets.AlarmSourceName=@eventSourceName of triggering         alarm     -   AND     -   mob_aots_tickets. OriginalProblemAbstract=@alarmCondition of         triggering alarm     -   AND     -   mob_aots_tickets.TicketState !=“Closed”|“Cancelled”         Depending on the query result, either service of aotsCreateTkt         or aotsUpdateTkt will be invoked Verification proposition         statements:     -   ( FUebDcae ∧ FUebDcae.out.eventDomain=‘fault’ ∧ ( TICKETINDB (         FUebDcae.out.eventSourceName, FUebDcae.out.alarmCondition )) →         FaotsUpdateTicket )     -   ( FUebDcae ∧ FUebDcae.out.eventDomain=‘fault’ ∧ ( ¬ ( TICKETINDB         ( FUebDcae.out.eventSourceName, FUebDcae.out.alarmCondition )))         → FaotsCreateTicket )     -   where TICKETINDB is Boolean function taking two arguments to         query DB for open tickets.         Input vectors can be partitioned into two Equivalence Classes.         Those input vectors in the first class have eventDomain=fault,         eventSourceName=AlarmSourceName of an existing open ticket and         alarmCondition=OriginalProblemAbstract of the ticket, which make         invocation to service AOTSUPDATETKT. On the other hand, those in         second class have eventDomain=fault and eventSourceName         !=AlarmSourceName of an existing open ticket and alarmCondition         !=OriginalProblemAbstract of the ticket, which make invocation         to service AOTSCREATETKT. Therefore, this test case may be split         into 2 test cases.

Test Case 1:

-   -   Service FUebDcae UEBDCAE_FAULT;     -   Boolean TicketInDB;     -   Service FaotsUpdateTicket AOTSUPDATETKT_FAULT;     -   Verification_section ( FUebDcae ∧         FUebDcae.out.eventDomain=‘fault’ ∧ ( TicketInDB (         FUebDcae.out.eventSourceName, FUebDcae.out.alarmCondition )) →         FaotsUpdateTicket )

Test Case 2:

-   -   Service FUebDcae UEBDCAE_FAULT;     -   Boolean TicketInDB;     -   Service FaotsCreateTicket AOTSCREATETKT_FAULT;     -   Verification_section ( FUebDcae ∧         FUebDcae.out.eventDomain=‘fault’ ∧ ( ¬ ( TicketInDB (         FUebDcae.out.eventSourceName, FUebDcae.out.alarmCondition ))) →         FaotsCreateTicket )         Similarly, from the branch of         eventDomain=thresholdCrossingAlert, the other two test cases can         be derived as below.

Test Case 3:

-   -   Service TUebDcae UEBDCAE_TCA.     -   Boolean TicketInDB;     -   Service TaotsUpdateTicket AOTSUPDATETKT_TCA;     -   Verification_section ( TUebDcae ∧         TUebDcae.out.eventDomain=‘thresholdCrossingAlert’ ∧ ( TicketInDB         ( TUebDcae.out.eventSourceName, FUebDcae.out.alarmCondition )) →         TaotsUpdateTicket )

Test Case 4:

-   -   Service TUebDcae UEBDCAE_TCA;     -   Boolean TicketInDB;     -   Service TaotsCreateTicket AOTSCREATETKT_TCA;     -   Verification_section ( TUebDcae ∧         TUebDcae.out.eventDomain=‘thresholdCrossingAlert’ ∧ ( ¬ (         TicketInDB ( TUebDcae.out.eventSourceName,         TUebDcae.out.alarmCondition ))) → TaotsCreateTicket )

Sample Use Case 2 Req. ID Design Element Trace-To HLD-285867-RUBY- Subscribe from the UEB to vMME Mobility-10 alarms published by DCAE-FM. Design Element Text RUBY-M shall subscribe from the UEB to DCAE-FM alarm messages. Subscription Topic: “DCAE-HIGHLANDPARK- EVENT-OUTPUT” By subscribing to this UEB topic, RUBY-M will receive published vMME alarm messages as well as other DCAE-FM alarm messages for other virtual devices. Fields of the DCAE-FM alarm message are defined in the DCAE-FM AID. Only UEB publish/subscribe service is involved in this use case. Initially, one would like to verify that ( UebDcae.in.eventSourceName=‘%mmex%’ ∨ UebDcae.in.eventSourceName=‘%MMEX%’→ UEBDcae ). Since there are two types of DCAE-FM alarms, Fault and TCA, the general test case could be divided into two test cases. For the first one ( UebDcae.in.eventDomain=‘fault’ ∧ ( UebDcae.in.eventSourceName=‘%mmex%’ ∨ UebDcae.in.eventSourceName=‘%MMEX%’) → UebDcae ) and for the second, ( UebDcae.in.eventDomain=‘thresholdCrossingAlert’ ∧ ( UebDcae.in.eventSourceName=‘%mmex%’ ∨ UebDcae.in.eventSourceName=‘%MMEX%’) → UebDcae ) These two test cases could further be split into the following four test cases as per mapping refinement described above.

Test case 1

-   -   Service FUebDcae UEBDCAE_FAULT;     -   Verification_section (( FUebDcae.in.eventDomain=‘fault’ ∧         FUebDcae.in.eventSourceName=‘%mmex%’ ∧ FUebDcae.in.send ) →         FUebDcae )

Test case 2

-   -   Service FUebDcae UEBDCAE_FAULT;     -   Verification_section (( FUebDcae.in.eventDomain=‘fault’ ∧         FUebDcae.in.eventSourceName=‘%MMEX%’ ∧ FUebDcae.in.send ) →         FUebDcae )

Test case 3

-   -   Service TUebDcae UEBDCAE_TCA;     -   Verification_section ((         TUebDcae.in.eventDomain=‘thresholdCrossingAlert’ ∧         TUebDcae.in.eventSourceName=‘%mmex%’ ∧ TUebDcae.in.send ) →         TUebDcae )

Test case 4

-   -   Service TUebDcae UEBDCAE_TCA;     -   Verification_section ((         TUebDcae.in.eventDomain=‘thresholdCrossingAlert’ ∧         TUebDcae.in.eventSourceName=‘%MMEX%’ ∧ TUebDcae.in.send ) →         TUebDcae )

In step 305 the application testing method 300 refines each test case of the first set of test cases to generate an updated set of executable test cases with propositional formulas. For each of test cases the method 300:

-   -   partitions input data into Equivalence Class Partitioning (ECP)         so that input in the same ECP results in the same output;     -   generates test cases so that input in each of ECP's is at least         covered by one test case; and     -   analyzes Boundary Value of input data and generate test cases so         that values that are at the boundaries and just inside/outside         of the boundaries are covered by at least one test case.

The generated test cases are executable scripts. The syntax of test cases is described using Backus-Naur Form as follows.

<Test Case> :: = <Verification process> <Verification process> :: = <Service_object_declare> <Verification section> | <Verification section> | <Verification section> < Verification process> | <Service_object_declare> <Verification section> < Verification process> <Verification section> :: = verification_section ( <Propositional statement> ); <Propositional statement> :: = <Composite Proposition> | <1-Connective sign> <Composite Proposition> <Composite Proposition> :: = <Atomic>| <Composite Proposition> <Connective symbol> <Composite Proposition> <Atomic> :: = TRUE | FALSE | <Identifier> <Comparison sign> <Expression> <Comparison sign> :: = = | > | < | ≥ | ≤ | ≠ <Expression> :: = <Var>|<Expression> <Arithmetic operator> <Expression> <Var> :: = <Identifier> | <Const> <Arithmetic operator> :: = + | − | * | / | % <Connective sign> :: = {circumflex over ( )} | v | → <1-Connective sign> :: = ¬ <Identifier> :: = <string> <string> :: = <string><char>|<String><digit>| <char>|<string><non-char><string> <non-char> :: = . | − | _(—) <Const> :: = <Const><digit>|<digit>|<digit->|-<digit-> <digit> :: = 0 | <digit-> <digit> :: = 1|2|3|4|5|6|7|8|9 <char> :: = a|b|c|d|e|f|g|h|i|j|k|l|m|n|o|p|q|r|s|t|u|v|w|x|y|z|      A|B|C|D|E|F|G|H|I|J|K|L|M|N|O|P|Q|R|S|T|U|V|W|X|Y|Z

In step 307 the application testing method 300 executes the updated set of test cases. For each test case one wants to prove p→q is TRUE for each of test cases. When executing a test case, TC interpreter 105 will first check the state of the related services to ensure p is TRUE. If p→q is FALSE, according to Truth Table, q must be FALSE. One then checks related service state for q and if it is TRUE, then it contradicts with that q must be FALSE. Thus, p→q is TRUE.

In step 309 the application testing method 300 interprets formulas based on related service states to verify if those formulas are satisfied. A service verification_section maps to a set of base verification functions invocations. A service verification_section may include, the following verification functions applying to a specified object or a subset of object attributes to determine if the testing propositional statements are satisfied. They are:

check request string lexical, syntactical and data type correctness;

check request name and attributes with HLD and macro definitions;

check request values with HLD;

check response string lexical, syntactical and data type correctness;

check response name and attributes verification with HLD and macro definitions; and

check response values with HLD, among others.

A verification function (VF) is a Boolean function with a proposition statement as an argument. The function returns a TRUE if the proposition's satisfaction is verified by function, otherwise, a False is returned. Combined propositional statement is split into a group of simple statements, each of which is used as an argument to call a VF. If all of VF's return a TRUE, then verification_section returns a TRUE. Otherwise, a FALSE is returned.

In step 311 the application testing method 300 may implement a regression test. Regression tests involve tailoring ranges of functional tests based upon requirements and then invoking test cases from test case libraries.

In step 313 the application testing method 300 may implement a load/stress test. Load/Stress tests are performed with such a paradigm that users browse the data in production database to choose preferred time period, and then framework extracts the data from production database, transforms the data format to fit replaying in a testing environment. The scripts for replaying are also automatically generated. The data will be replayed with original timing and concurrency so that user can rapidly duplicate and test many real-life scenarios.

In step 315 the application testing method 300 may implement a functional test. For user stories in each of iteration or use cases in high level design, generate test cases. For each of test cases, specify service objects under test and define a verification statement. The framework will generate executable test cases and interpret them at run time so that each user story or use case has a mapping set of test cases. In the whole systems development life cycle (SDLC), if new features need to be delivered and integrated into an existing release, the corresponding test cases can be generated and executed. All of test cases form a test case library and the subset of test cases in the library can be invoked and reused for similar user stories or use cases.

FIG. 4 is a flowchart of a method 400 for generating test cases.

In step 401 use cases for the application under test are identified.

In step 403 conditional branches for a given use case are identified.

In step 405 a determination is made about whether all branches have been identified. If all branches have not been identified then the method returns to step 403.

If all branches have been identified then in step 407 for a branch in a branch set, the service flow, input and output are identified.

In step 409 a propositional statement using input and output is identified.

In step 411 the branch is mapped to a test case.

In step 413 a determination is made as to whether all branches of been processed. If all branches have not been process than the method returns to step 407.

If all branches have been processed, then in step 415 for a generated test case and input ECP is used to generate more test cases (updated set of test cases) and to add them to the first set of test cases.

In step 417 a determination is made if all test cases have been processed. If all test cases have not been processed then the method returns to step 415.

If all test cases have been processed, then in step 419 input boundary values are used to generate additional test cases and to add them to the test case set.

In step 421 a determination is made if all test cases have been processed. If all test cases have not been processed then the method returns to step 419.

If all test cases have been processed, then in step 423 a set of all test cases is stored.

The methods described in the examples may be embodied directly in hardware, in a software module executed by a computer system having a processor, or in a combination of the two. A software module may reside in any form of memory or storage medium such as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM. The memory or storage medium may be coupled to the processor such that the processor can read information from, and write information to, the memory or storage medium. Alternatively, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. In some aspects, the steps and/or actions of a method may reside as one or any combination or set of codes and/or instructions on a machine readable medium and/or computer readable medium, which may be incorporated into a computer program product.

In any of the exemplary embodiments, the described functions may be implemented in hardware, software, firmware, or any combination thereof. Functions implemented in software may be stored on or transmitted over as instructions or code on a non-transitory computer-readable medium. A non-transitory computer readable medium may include computer executable instructions embodied in a computer readable medium that when executed by the processor of a computer performs the steps of the method. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

The previous description of the disclosed examples is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these examples will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other examples without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the examples shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein. 

1. A method of testing a service-based application comprising: generating a service flow for the service-based application; converting the service flow into a use case; associating, with a test case generator the use case with a first set of executable test cases, wherein each executable test case in the first set of executable test cases comprises an executable script; transforming each of the test cases in the first set of test cases into an updated set of test cases with propositional statements that are abstracted from the service flow including service input and output conditions; executing the updated test cases; and evaluating the propositional statements to determine success or failure of each of the updated set of test cases.
 2. The method of claim 1 wherein associating the use case comprises: determining conditional branches for the use case; determining a service flow for each of the conditional branches; determining input and output conditions for each of the conditional branches; associating each of the conditional branches to one of the first set of executable test cases; and determining propositional statements as verification logic for each test case based on input and relating services.
 3. The method of claim 1 wherein transforming each of the test cases comprises: partitioning input data into Equivalence Class Partitioning (ECP) so that input in an ECP results in a same output generating a first subset of the updated set of test cases so that input in each of ECP's is at least covered by one test case; and analyzing a Boundary Value of input data and generating a second subset of the updated set of test cases so that values that are at a boundary and just inside/outside of the boundary are covered by at least one test case.
 4. The method of claim 1 wherein executing the updated set of test cases comprises applying a verification function to the updated set of test cases.
 5. The method of claim 1 further comprising performing a functional test for each of the tests cases in the updated set of test cases.
 6. The method of claim 1 further comprising performing a load/stress test for each of the tests cases in the updated set of test cases.
 7. The method of claim 1 further comprising performing a regression test for each of the test cases in the updated set of test cases.
 8. A system for testing a service based application comprising: a computer system; a test case generator associated with the computer system for generating executable test cases with propositional statements; a test case interpreter for interpreting the propositional statements generated by the test case generator by checking a state of services under test; a service specification acquisition module for acquiring all service specifications; and a basic functions library associated with the computer system; and a memory coupled to the computer system and configured to store program instructions executable by the computer system to: generate a service flow for the service-based application; convert the service flow into a use case; associate, with the test case generator the use case with a first set of executable test case cases wherein each executable test case in the first set of executable test cases comprises an executable script; transform each of the test cases in the first set of test cases into an updated set of test cases with propositional statements that are abstracted from the service flow and service input and output conditions; execute the updated set of test cases using the test case interpreter; and evaluate the propositional statements to determine success or failure of each of the updated set of test cases.
 9. The system of claim 8 further comprising a graphical user interface for entering use cases.
 10. The system of claim 8 wherein the propositional statements are abstracted from service-flow and service input and output conditions.
 11. The system of claim 8 wherein the test case interpreter performs lexical, syntactical and type check on the executable test cases.
 12. The system of claim 8 further comprising a simulator module coupled to the test case interpreter and the basic functions library.
 13. The system of claim 8 further comprising a test case library coupled to the test case interpreter.
 14. The system of claim 8 further comprising a service object store coupled to the test case generator.
 15. Non-transitory computer readable medium comprising computer executable instructions embodied in a computer readable medium and when executed by a processor of a computer performs steps comprising: generating a service flow for the service-based application; converting the service flow into a use case; associating, with a test case generator the use case in with a first set of executable test cases wherein each executable test case in the first set of executable test cases comprises an executable script; transforming each of the test cases in the first set of test cases into an updated set of test cases with propositional statements that are abstracted from the service flow including service input and output conditions; executing the updated set of test cases; and evaluating the propositional statements to determine success or failure of each of the updated set of test cases.
 16. The non-transitory computer readable medium of claim 15 wherein associating the use case comprises: determining conditional branches for each use case; determining a service flow for each of the conditional branches; determining input and output conditions for each of the conditional branches; associating each of the conditional branches to one of the first set of executable test cases; and determining propositional statements as verification logic for each test case based on input and relating services.
 17. The non-transitory computer readable medium of claim 15 wherein transforming each of the test cases comprises: partitioning input data into Equivalence Class Partitioning (ECP) so that input in an ECP results in a same output generating a first subset of the updated set of test cases so that input in each of ECP's is at least covered by one test case; and analyzing a Boundary Value of input data and generating a second subset of the updated set of test cases so that values that are at a boundary and just inside/outside of the boundary are covered by at least one test case.
 18. The non-transitory computer readable medium of claim 15 wherein executing the updated set of test cases comprises applying a verification function to the updated set of test cases.
 19. The non-transitory computer readable medium of claim 15 further comprising computer executable instructions embodied in a computer readable medium and when executed by a processor of a computer performs a further step of performing a functional test for the updated set of test cases.
 20. The non-transitory computer readable medium of claim 15 further comprising computer executable instructions embodied in a computer readable medium and when executed by a processor of a computer performs a further step of performing a load/stress test for the updated set of test cases. 